This article shows how to use map projections in the ggplot package and uses this to demonstrate that the world is not flat.
We all hate the experience of calling a service provider and being placed on hold for a very long time. Organisations that take their level of service seriously plan their call centres so that the waiting times for customers is within acceptable limits. Having said this, making people wait for something can in some instances increase the level of perceived value.
Call centre performance can be expressed by the Grade of Service, which is shown in the percentage of calls that are answered within a specific time, for example, 90% of calls are answered within 30 seconds. This Grade of Service depends on the volume of calls made to the centre, the number of available agents and the time it takes to process a contact. Although working in a call centre can be chaotic, the Erlang C formula describes the relationship between the Grade of Service and these variables quite accurately.
This article explains how to use the Erlang C formula in the R language to manage a contact centre by calculating the number of agents needed to meet a given service level. This approach is extended with a Monte Carlo situation to understand the stochastic nature of the real world better.
Euler Problem 33 takes us back to the world of fractions from our primary school days. This article explains how to solve Euler Problem 33 with R and shows how to use a seqence of fractions to draw Ford Circles.
Emacs is the swiss-army chainsaw of software, the ultimate killer app. This article explains the basics of using R with Emacs and ESS, including an example of literate programming in Org Mode.
This article describes how to scrape a website to analyse 72 definitions or marketing, collected by Heidi Cohen, using the Rvest and Tidytext packages in the R language.
This article provides a solution in the R language for Euler Problem 144: How many times does a laser bounce inside an elliptical mirror before the light beam exits it? We can use the solution to this problem to simulate elliptical billiard tables.
How can R be used to conduct qualitative data science? An example analyses interviews with customer advocacy groups and regulators of water utilities using the RQDA package.
Various methods to approximate and visualise the digits of pi using the R computing language for statistics. The apparent randomness of the decimal expression of Pi is a source for beautiful visualisations.
Can we use data science to find out more about how people feel about tap water and learn about the reasons behind this loss in trust in the municipal water supply?
Topology is the silly putty of mathematics. One of the strangest shapes in topology is the Möbius strip. This strip is a surface with only one side. This article shows how the visualise this shape in R using the RGL package.
Many water utilities are implementing or considering digital metering. This article describes analysing digital water meter data using the data science Tidyverse library.
This article simulates water consumption to assist with developing leak detection algorithms. Simulating water consumption helps to develop business tools.